Systems capable of delivering human and object motion currently exist but are typically very sophisticated and expensive. As well, the format of the feedback provided by these systems varies considerably. Typically, there are no exhaustive methods and systems to deliver biomechanical feedback across multiple platforms and entities consistently. For example, optical motion capture is currently used in motion capture studios and sports technology companies to analyze humans and objects. These motion capture laboratories and studios focus on biomechanical research of human subjects to analyze performance, recovery, and injury risk identifiers, amongst others. Many biomechanical researchers develop proprietary software and processing algorithms to extract kinematic and kinetic measures of human and object motion. The application of physics engines to extract these metrics are based on the precision and location of retro-reflective markers on bony anatomical landmarks of the body and objects. Feedback is usually given in highly technical formats that often leave the test-subject unaware of the true underlying biomechanical flaw and fail to address corrective exercises, drills, and training regimens to improve performance and recovery, and reduce the risk of injury. As well, when and if prescriptive feedback is given, there are few methods to assess compliance with such feedback and there are few systems available for appropriate re-evaluation of the human subject and object.
Accordingly, a need exists for a system that provides biomechanical feedback in a format which is usable by an actor/athlete to improve their performance and reduce their risk of injury and that is supported by statistical relationship models, interactive platforms, and more advanced hardware platforms.
Wearable technology is becoming a primary means of assessing human and object motion. This technology is based upon embedding sensor technology in wearable garments. An example of such use is the ability to extract data from one or more on miniaturized accelerometers and gyroscopes for the purpose of reconstructing three-dimensional motion, however, there are limitations to the precision and accuracy of wearable technology that often misleads users with information that is not supported by statistical models. Wearable technology also does not provide comprehensive motion detection of all body and object segments, and, thus, does not allow for extensive prescriptive feedback to improve performance and recovery, and, thereby, reduce the risk of injury. Wearable technology is often wirelessly interfaced with mobile devices to compute kinematics and kinetics, and to display biomechanical feedback in single sessions. That said, there is no cross-platform continuity to keep users engaged, and few methods to monitor compliance and deliver significant feedback.
Accordingly, a further need exists for a system that incorporates advanced physics engine capabilities, advanced hardware processing and sensor technology, and interactive interfaces to produce meaningful data usable by an actor/athlete to improve their performance and reduce their risk of injury.